A nomogram based on psoas muscle index predicting long-term cirrhosis incidence in non-cirrhotic patients with HBV-related acute‑on‑chronic liver failure

There is a lack of scoring system to predict the occurrence of cirrhosis in individuals with acute-on-chronic liver failure (ACLF) in the absence of cirrhosis. The goal of this study was to develop a psoas muscle index (PMI)-based nomogram for cirrhosis risk in non-cirrhotic patients with HBV-related ACLF. We included 274 non-cirrhotic HBV-ACLF patients who were randomly assigned to training and validation groups. Logistic analyses were performed to identify risk factors for cirrhosis. A nomogram was then constructed. The predictive performance of the nomogram was assessed using the area under the receiver operating characteristic curve (AUROC), calibration curve, and decision curve analysis (DCA). During the 360-day follow-up, 44.5% (122/274) of non-cirrhotic HBV-ACLF patients developed cirrhosis. A higher PMI at the L3 level was correlated with a decreased risk of long-term cirrhosis occurrence (OR 0.677, 95% CI 0.518–0.885, P = 0.004). The nomogram incorporating PMI, age, neutrophil-to-lymphocyte ratio (NLR), and international normalized ratio (INR), indicated satisfactory predictive performance for cirrhosis risk stratification in ACLF population. The nomograms had an AUROC of 0.812 (95% CI 0.747–0.866) and 0.824 (95% CI 0.730–0.896) in the training and validation cohorts, respectively. The calibration curves displayed excellent predictive accuracy of the nomogram in both sets. In both cohorts, the DCA verified the nomogram's clinical efficacy. In non-cirrhotic HBV-ACLF patients, a greater PMI appears to protect against long-term cirrhosis occurrence. Strong predictive performance has been demonstrated by PMI-based nomograms in assessing the likelihood of 1-year cirrhosis in those with HBV-ACLF.


Evaluation of Psoas Muscle Index
Within 2 weeks of the diagnosis of ACLF, all enrolled patients underwent abdominal CT scans manufactured by Siemens AG, Germany.Two imaging specialists independently evaluated the lumbar muscle area (cm 2 ) at the L3 cross-section of the CT image using the 3D Slicer program (version 5.1.0).A third doctor was brought in to resolve any differences that arose.The patient's height (m 2 ) divided by the area of the psoas muscle at the L3 level was used to compute PMI 14,15 .

Statistical analysis
MedCalc software (version 20.1.0),IBM SPSS Statistics (version 22.0), and R software (version 4.1.2) were used for statistical analyses.The study comprised 274 patients, with 183 randomly allocated to the training cohort to generate the prediction model and the remaining 91 patients assigned to the validation group to test model performance.Quantitative data that were normally distributed were subjected to the unpaired t-test, whereas non-normally distributed data were subjected to Mann-Whitney U tests.The comparisons between the categories of categorical variables were analyzed using the Chi-square test.
For the training cohort, univariate logistic regression analysis was used to find putative cirrhosis predictors.The multivariate regression model only contained variables that had a P value 0.05 in the univariate analysis.An independent predictor-based nomogram was created in the R software, utilizing the rms library.Utilizing the area under the receiver operating characteristic curve (AUROC), the discriminatory performance of the developed models was compared.Model calibration was performed by plotting calibration curves of true probabilities against model predicted probabilities.To determine net benefits, decision curve analysis (DCA) was performed.The threshold for statistical significance was set at P < 0.05.

Patients' baseline characteristics
A total of 274 HBV-ACLF patients without cirrhosis were included in this study.Patients' mean PMI was 6.4 ± 1.5 cm 2 /m 2 , and their average age was 46.4 ± 13.8 years overall (Table S1).The mean MELD and MELD-Na scores were 24.5 ± 4.1 and 24.9 ± 4.1, respectively.ACLF susceptibility factors for all patients were detailed in Table S2.
During the follow-up period of at least 1 year, cirrhosis was diagnosed in 122 (44.5%) patients.
We performed univariate and multivariate logistic regression analysis to find possible variables connected to the long-term development to cirrhosis in HBV-ACLF patients.Age, PMI, WBC, NLR, INR, TB, ALB, ChE, Na, and AFP were significantly linked with progression to cirrhosis in ACLF patients, according to the results of the univariate analysis (P < 0.05), as presented in Table 2. Table 2 also includes the findings of the multivariate logistic analysis, which demonstrated that patients with HBV-ACLF had a lower risk of developing cirrhosis if they had higher PMI levels after 360 days of follow-up, with an odds ratio (OR) of 0.677 (95%CI 0.518-0.885,P = 0.004).In addition, age, NLR, and INR all contributed to an increased incidence of cirrhosis (P < 0.05).www.nature.com/scientificreports/

Construction of PMI-based nomogram for long-term progression to cirrhosis
We then developed a nomogram using the four independent predictors mentioned above, namely PMI, age, NLR, and INR (Fig. 1).The patient's score was determined by summing the scores from the four risk variables, which were obtained using the vertical axis of each risk indicator.The probability of developing cirrhosis for each individual was then acquired from the "Total Points" axis of the nomogram.

Discussion
To our knowledge, this is the first research to exam how PMI could affect non-cirrhotic HBV-ACLF patients' long-term (1 year) progression to cirrhosis.Our research suggests that a higher PMI at L3 may prevent the development of cirrhosis.We have also developed a PMI-based nomogram for cirrhosis risk stratification in HBV-ACLF patients.This nomogram demonstrated good predictive performance for the occurrence of cirrhosis in non-cirrhotic HBV-ACLF patients at baseline.By weighing the likelihood of cirrhosis occurrence, these patients can be identified in advance and individualized clinical management could be optimized during the recovery.Despite the fact that there is no consensus definition for ACLF, it is widely acknowledged to be a complicated clinical condition marked by abrupt hepatic deterioration in CLD, along with organ failure and substantial shortterm death rates [18][19][20] .The Asia Pacific consortium has defined ACLF as acute liver failure following acute hepatic insult in patients with underlying CLD or cirrhosis 1 .However, while many prior studies have concentrated primarily on mortality in ACLF individuals, liver reserve during recovery and long-term clinical outcomes in survivors, has been overlooked largely.In fact, due to severe acute liver decompensation and imbalance in injury as well as regeneration, a subset of non-cirrhotic ACLF patients can gradually develop irreversible cirrhosis with quality of life and longevity impacted.There are currently no scoring models for non-cirrhotic ACLF patients that can predict the long-term incidence of cirrhosis.In this study, we explored various risk variables affecting longterm (1-year) progression to cirrhosis in HBV-ACLF patients.Our findings suggest that the risk of long-term cirrhosis in HBV-ACLF individuals is substantially linked to increased age, NLR, and INR as well as lower PMI.
Sarcopenia, a form of malnutrition, can affect up to 70% of advanced liver disease patients 21 .In recent years, sarcopenia's impact on patients with CLD has gained significant attention.Studies have established a strong correlation between sarcopenia and liver disease severity 9,[22][23][24] , with sarcopenia effectively predicting unfavorable outcomes, particularly in cirrhosis patients 7,25,26 .Sarcopenia has been associated to liver fibrosis in those with non-alcoholic fatty liver disease (NAFLD) 27,28 .Patients with significant fibrosis have lower SMI than those without 29 ; low SMI acted as an independent predictor of advanced liver fibrosis 29,30 .Recent studies have also shown that lower PMI or SMI at L3 level is highly correlated with increased mortality risk in ACLF patients 10,11,13 .In non-cirrhotic HBV-ACLF patients, our research revealed a link between PMI and long-term cirrhosis development.The results remained consistent after taking into account additional significant variables in a multifactorial logistic regression analysis.
The underlying biological mechanism linking sarcopenia to ACLF progression remains incompletely understood.However, evidence suggests that ACLF is accompanied by intense systemic inflammation and oxidative stress, which can disrupt the delicate equilibrium between protein synthesis and breakdown 31,32 .Additionally, hyperammonemia resulting from severe liver dysfunction can lead to muscle wasting through the upregulation of myostatin, an important myokine involved in the muscle-liver crosstalk 6 .This crosstalk involves the secretion of various cytokines and proteins by skeletal muscle that may affect other tissues, including the liver 33 .Studies have shown that myostatin activates hepatic stellate cells via the JNK signaling pathway, which leads to liver fibrosis 34 .Other molecular factors, such as irisin and vitamin D, also significantly impact muscle-liver crosstalk 35 .Therefore, muscle dysfunction could accelerate the advancement of liver disease, including ACLF, and low PMI may be a contributing factor to poor outcomes, such as progression to cirrhosis.
Age is a primary and immutable risk factor for the advancement of CLD, such as NAFLD, hepatic fibrosis, cirrhosis, and liver cancer 36,37 .Liver ageing can exacerbate necrotic apoptosis and chronic inflammation in the liver, which in turn leads to liver fibrosis and other CLD 38 .NLR is a simple and well-defined marker of immune dysregulation.High NLR level indicates poor prognosis of ACLF after the liver transplantation 39 .It has been reported that among cirrhotic individuals, a higher NLR is linked to a 9% rise in the probability of death within a year 40 .It is possible that the predictive power of NLR addresses multiple pathways in the pathogenesis of CLD, involving the triggering of mild endotoxemia, and eliciting detrimental systemic inflammatory response.Thus, aging and high NLR levels can lead to progression to cirrhosis in ACLF patients not affected with cirrhosis.INR serves as a key index for diagnosing ACLF, reflecting both the liver injury and coagulation abnormality.Our findings are consistent with a few previous studies that found a possible connection between INR and adverse outcomes due to liver failure 1,41,42 .Additionally, INR was shown to be able to predict fibrosis in individuals with chronic hepatitis B 43 .Our findings provide additional evidence that INR contribute to cirrhosis development in ACLF subjects without pre-existing cirrhosis.
In this study, we discovered that PMI-based nomograms outperformed MELD and MELD-Na scores at predicting the long-term risk of cirrhosis in patients with non-cirrhotic HBV-ACLF.This may be explained by the fact that MELD and MELD-Na scores are designed for those with severe end-stage liver disease, while our study included non-cirrhotic ACLF patients.This could also be due to the strong association reported between sarcopenia and cirrhosis, which was neglected by MELD and MELD-Na scores.The nomogram can effectively guide the frequency of the follow-up and the decision related to initiation of nutritional intervention.Higher nomogram scores might lead to recommendations for more frequent follow-up and more aggressive nutritional intervention for greater benefit.Our DCA results indicated that more patients with HBV-ACLF could benefit from the timely and appropriate treatment when the threshold probability of the nomogram was > 3%.
The current study has certain limitations.First, it was retrospective in nature, thus resulting in inherent bias in the results.Second, all the subjects and their clinical information were obtained from a single center and external validation was lacking.Third, this study only analyzed the possible effect of baseline PMI on outcome, but the dynamic alterations of PMI were not taken into consideration.Lastly, the liver status prior to ACLF, particularly the extent of liver fibrosis, affects the risk of cirrhosis during the recovery period.Unfortunately, this study lacks data on this aspect.Therefore, the impact of PMI on the prognosis of ACLF lacks adequate assessment.Hence, multicenter prospective studies could be performed in future to further verify the robustness and applicability of our conclusions.

Figure 1 .Figure 2 .
Figure 1.The nomogram used to predict the risk of cirrhosis in the training cohort.PMI, psoas muscle index; NLR, neutrophil-to-lymphocyte ratio; INR, International normalized ratio.

Figure 3 .
Figure 3.The calibration curve of nomogram.(A) Mean absolute error was found to be 0.021 for the training set; (B) Mean absolute error was noted to be 0.026 for the validation cohort.

Figure 4 .
Figure 4.The decision curves of the nomogram, MELD and MELD-Na scores in the training set (A) and validation set (B). MELD, Model for end-stage liver disease.
https://doi.org/10.1038/s41598-023-47463-4www.nature.com/scientificreports/In summary, our study revealed that among non-cirrhotic HBV-ACLF patients, a lower PMI is independently correlated with the development of cirrhosis.The PMI-based nomogram can be a useful tool for assessing the likelihood of cirrhosis in non-cirrhotic HBV-ACLF patients at 1 year.

Table 1 .
Comparison of the baseline characteristics between cirrhosis and non-cirrhosis groups in the training cohort.